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Salesforce Einstein Features
13Apr

Salesforce Einstein Features

Salesforce Einstein Discover the power of the #1 AI for CRM with Einstein. Built into the Salesforce Platform, Einstein uses powerful machine learning and large language models to personalize customer interactions and make employees more productive. With Einstein powering the Customer 360, teams can accelerate time to value, predict outcomes, and automatically generate content within the flow of work. Einstein is for everyone, empowering business users, Salesforce Admins and Developers to embed AI into every experience with low code. Salesforce Einstein Features. Einstein Copilot Sales Actions: Sell faster with an AI assistant in the flow of work.Call Exploration: Ask Einstein to synthesize important call information in seconds. Ask Einstein to identify important takeaways and customer sentiment, so you have the context you need to move deals forward.

 Sales Summaries: Summarize records to identify likelihood the deal will close, the competitors involved, key activities, and more. Forecast Guidance: Ask Einstein to inform your forecast and help you identify which deals need your attention. Close Plan: Generate a customized action plan personalized to your customer and sales process. Increase conversion rates with step-by-step guidance and milestones grounded in CRM data. Salesforce Einstein Features Sales Generative AI features: ° Knowledge Creation: ° Search Answers for Agents and Customers: Einstein Copilot Service Actions: Streamline service operations by drafting Knowledge articles and surfacing answers, grounded in knowledge, to the most commonly asked questions. Summarize support interactions to save agent time and formalize institutional knowledge. Surface generated answers to agents’ & customers’ questions that are grounded in your trusted Knowledge base directly into your search page. Search Answers for Agents is included in the Einstein for Service Add-on SKU and Search Answers for Customers is included in the Einstein 1 Service Edition.
Empower agents to deliver more personalized service and reach resolutions faster with an AI assistant built into the flow of work. You can leverage out-of-the-box actions like summarize conversations or answer questions with Knowledge or you can build custom actions to fit your unique business needs. Service Salesforce Einstein Features This Release Einstein CopilotSell faster with an AI assistant. No data requirements
Included in Einstein 1 Sales Edition.hEinstein Copilot: Sales ActionsSell faster with an AI assistant.No data requirements. 
 Call explorer and meeting follow-up requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Generative AIBoost productivity by automating time-consuming tasks.No data requirements. 
 Call summaries and call explorer requires Einstein Conversation Insights.
Included in Einstein 1 Sales Edition. Einstein will use a global model until enough data is available for a local model. For a local model: ≥1,000 lead records created and ≥120 of those converted in the last 6 monthsEinstein Automated Contacts Automatically add new
contacts & events to your CRM≥ 30 business accounts. If you use Person Accounts, >= 50 percent of accounts must be business accounts Einstein Recommended ConnectionsGet insights about your teams network to see who knows your customers and can help out ona deal ≥ 2 users to be connected to Einstein Activity Capture
and Inbox (5 preferred) Einstein Forecasting Easily predict sales forecasts inside
of Salesforce Collaborative Forecasting enabled; use a standard fiscal year; measure forecasts by opportunity revenue; forecast hierarchy must include at least one forecasting enabled user who reports to a forecast manager; opportunities must be in Salesforce ≥ 24 months;Einstein Email Insights Prioritize your inbox with actionable intelligence Einstein Activity Capture enabledEinstein Activity Metiics (Activity 360) Get insight into the activities you enter
manually and automatically from Einstein
Activity Capture Einstein Activity Capture enabled Sales Analytics Get insights into the most common sales KPIs No data requirements. User specific requirements like browser and device apply Einstein Conveisation Insights Gain actionable insights from your sales calls with conversational intelligenceCall or video recordings from Lightning Dialer, Service Cloud Voice, Zoom and other supported CTI audio and video partners.Buyer Assistant Replace web-to-lead forms with real-time conversations. No data requirements – Sales Cloud UE or Sales Engagement. Einstein Opportunity ScoringEinstein Activity CaptuiePrioritize the opportunities most likely to convertAutomatically capture data & add to your CRMEinstein will use a global model until enough data is available for a local model. For a local model: ≥ 200 closed won and ≥ 200 closed lost opportunities in the last 2 years, each with a lifespan of at least 2 days≥ 30 accounts, contacts, or leads; Requires Gmail, Microsoft Exchange 2019, 2016, or 2013 Einstein Relationship Insights Speed prospecting with AI that researches for you. No data requirements. Einstein Next Best Action Deliver optimal recommendations at the point of maximumimpactNo data requirements. User specific requirements like browser and device apply Sales AIGenerate emails, prioritize leads & opportunities most likely to convert, uncover pipeline trends, predict sales forecasts, automate data capture, and more with Einstein for Sales. Generative AIPrompt BuilderEinstein Lead ScoringEinstein Opportunity ScoringEinstein Activity CaptureEinstein Automated ContactsEinstein Recommended ConnectionsEinstein ForecastingEinstein Email InsightsEinstein Activity Metrics (Activity 360)Sales AnalyticsEinstein Conversation InsightsBuyer Assistant Sales AIGenerative AI: 
Feature Why is it so Great? What do I need? Automate common questions and business processes to solve customer requests fasterBoost productivity by auto-generating service replies, summarizing conversations during escalations andtransfers or closed interactions, drafting knowledge articles, and surfacing relevant answers grounded inknowledge for agents’ and customers’ commonly asked questions. Deliver optimal recommendations at the point of maximum impactEliminate the guesswork with AI-powered recommendations for everyoneDecrease time spent on manual data entry for incoming cases and improve case field accuracy and completionAutomate case triage and solve customer requests fasterDecrease time spent selecting field values needed to close a case with chat conversations and improved field accuracySurface the best articles in real time to solve any customer’s questionEliminate time spent typing responses to the most common customer questionsGet insights into contact center operations, understand customers, and deliver enhanced customerexperiencesChat or Messaging channels, minimum of 20 examples for most languagesNo data requirements. User specific requirements like browser and device apply Make sure that your dataset has the minimum records to build a successful recommendation. Recipient Records need a minimum of 100 records,Recommended Item Records need a minimum of 10 records, andPositive Interaction Examples need a minimum of 400 records

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April 13, 2024in Generative AI, Salesforce Einstein, Snowflake
Top AI Tools Shaping Business Success
19Mar

Top AI Tools Shaping Business Success

Top AI Tools Shaping Business Success in 2024 In the dynamic world of business, staying ahead means embracing the latest technologies. Artificial Intelligence (AI) is no longer just a buzzword—it’s a transformative force that helps businesses operate more efficiently, make smarter decisions, and enhance customer experiences. As we move through 2024, the AI tool ecosystem is rapidly expanding, offering innovative solutions to automate tasks, gain deep insights, and improve customer engagement. Below, we explore the top AI tools that are shaping the future of business. StoryChief is a comprehensive content marketing platform that simplifies the creation and distribution of content through AI. From ideation to optimization, it leverages machine learning to help businesses generate high-quality, engaging content at scale. Key Features: Pricing: Plans start with a free tier, with paid options ranging from $40 to $500 per month. Developed by OpenAI, ChatGPT is a versatile language model capable of generating human-like text. It excels in content creation, customer support, and data analysis. Key Use Cases: Pricing: API access with usage-based pricing. Perplexity AI is an advanced search engine that provides accurate, summarized answers to complex queries using natural language processing (NLP). Key Features: Pricing: Free version available, with Pro version at $20/month offering enhanced features. Zapier connects over 5,000 apps, enabling automation of repetitive tasks across your tech stack with AI-powered tools that simplify complex automations. Key Features: Pricing: Free plan available for up to 100 tasks per month; paid plans start at $19.99/month. Grammarly is an AI-driven writing assistant that enhances the quality of written communication, ensuring clarity, conciseness, and error-free content. Key Features: Pricing: Free version available; Premium plans start at $12/month for individuals and $25/user/month for businesses. Typeframes simplifies video creation with AI, turning scripts or images into professional-quality videos with animations, transitions, and voiceovers. Key Features: Pricing: Plans start at $29/month, with higher-tier options available. Chatbase enables businesses to build intelligent chatbots and virtual assistants that handle a wide range of customer service inquiries. Key Features: Pricing: Free plan available with limited message credits; paid plans start at $19/month. Secta is an AI-powered headshot generator that creates professional-quality headshots from user-submitted photos, ideal for businesses needing polished profile pictures. Key Features: Pricing: Pay-as-you-go at $49 per headshot session. Voicenotes is an AI-driven transcription tool that converts voice memos into concise summaries and action items, perfect for capturing important information efficiently. Key Features: Pricing: Free plan available; paid plans start at $10/month, with lifetime payment options. Notion AI enhances the popular Notion productivity platform with AI-powered writing assistance, content summarization, and database management. Key Features: Pricing: Available as an add-on at $10 per user per month, with discounts for annual plans. Choosing the Right AI Tools for Your Business Selecting the right AI tools involves considering several factors: By evaluating these aspects, you can effectively leverage AI to enhance efficiency, drive growth, and maintain a competitive edge in 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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March 19, 2024in Salesforce
Service and Generative AI
08Mar

Service and Generative AI

Customer service organizations are currently grappling with formidable challenges, as service agents contend with unprecedented case volumes and customers increasingly express frustration over extended wait times. Agents often find themselves managing multiple customer issues simultaneously, awaiting data from legacy systems to load, leading to inefficiencies. Service and Generative AI together are a solution to better serve your customers. The closure of a case does not mark the end of the challenge, as case notes may go missing, and subsequent agents may unknowingly address similar issues from scratch. With nearly half of customers citing poor service experiences as a primary reason for switching brands, companies are under immense pressure to find more effective solutions. Recent excitement surrounds ChatGPT, an artificial intelligence (AI) model by OpenAI. Models like GPT, Anthropic, and Bard, constructed on large language models, hold the potential to revolutionize customer service. Combined with Salesforce’s established AI expertise, generative AI models are poised to transform customer service operations, enhancing efficiency, fostering empathetic responses, and expediting case resolutions. Here’s a glimpse into how generative AI could reshape service operations: Automated Personalized Responses: Integrating generative AI with Einstein for Service and Customer 360 allows companies to automatically generate personalized responses, enabling agents to promptly communicate with customers. AI training across all case notes facilitates the creation of knowledge articles, significantly reducing the time to produce knowledge and enabling easier updates. Field Service Enhancements: Generative AI will benefit frontline service teams with automated reports, assist new employees and contractors in onboarding and ongoing learning, and empower customers to troubleshoot common issues with knowledge base articles. Super-powered Chatbots: Layering generative AI on Einstein capabilities automates the creation of intelligent, personalized chatbot responses, enhancing the understanding and anticipation of customer issues. This approach improves first-time resolution rates and allows organizations to drive continuous improvement through sentiment analysis and pattern identification.  Conversational bots that are powered by generative AI can power customer self-service and improve customer satisfaction — by ensuring case-specific tonality and context in real time. Auto-generate Knowledge Articles: Generative AI will draft knowledge articles based not only on case notes but also on Slack conversations, messaging history, and data across Customer 360, accelerating agent case resolution and increasing support cases in self-service experiences. Fast-track Case Swarming: Generative AI identifies past cases similar to ongoing complex issues, recommends experts within the organization to address the problem, and suggests resolutions and customer communications. This streamlines case swarming processes, making them more efficient and, in some cases, automating aspects of the process. Customer Service and Generative AI While generative AI presents tremendous opportunities, human oversight is essential due to the potential for biased or harmful outputs. Salesforce has published guidelines for trusted generative AI development, emphasizing ethical considerations. As we enter this new era of AI, guided by Salesforce’s commitment to ethical product development, organizations can leverage generative AI to boost productivity, accelerate case resolution, and enhance customer relationships with greater personalization and relevance. Like1 Related Posts Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more Salesforce’s Quest for AI for the Masses The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Read more Salesforce Inbox Explained Salesforce Inbox explained. Enhance the productivity of sales reps with Inbox features, enabling efficient management of every email message, whether Read more

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March 8, 2024in Generative AI, Salesforce Service Cloud
Conversational Commerce
20Feb

Conversational Commerce

“Hey Siri, find the top-rated red saddle pads.” This simple command exemplifies how conversational commerce is revolutionizing the digital shopping experience. While Siri and Alexa are training us to talk to our technology, traditional chatbots teach us to ask our technology in natural language to do something. Now, customers can utilize chatbots, messaging apps, and voice assistants to explore products and complete purchases online. This experiential shopping shift enables businesses to engage with consumers in a natural manner, seamlessly integrating into their everyday routines. With conversational AI, shopping feels akin to conversing with a friend. Thanks to advancements in generative AI, the process is becoming increasingly personalized, intuitive, and hassle-free. Here’s an overview of conversational commerce: What is conversational commerce? Conversational shopping tools involve enhancing sales through direct communication with customers. It encompasses automated conversation flows as well as interactions between sales and service representatives and customers via text or social media messaging. Ultimately, conversational commerce aims to establish meaningful, personalized connections with customers, combining the convenience of digital communication with the warmth of human language to drive sales and foster loyalty. Different Types of Conversational Commerce: The Role of AI in Conversational Commerce: AI plays a primary role in evolving conversational commerce by understanding consumer intent and guiding them through the purchasing process. Natural language processing (NLP) enables chatbots to comprehend inquiries and provide relevant responses, while machine learning analyzes customer data to offer personalized recommendations and streamline the purchase journey. Conversational Commerce and Social Commerce: Conversational commerce intersects with social commerce, capitalizing on platforms like Instagram and TikTok to build authentic connections with customers and facilitate seamless transactions embedded in their social interactions. Benefits of Conversational Commerce: Common Pitfalls and Solutions: By leveraging conversational commerce effectively, businesses can create seamless, personalized interactions that drive sales and foster long-term customer relationships. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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February 20, 2024in Generative AI, Salesforce Development Services, Salesforce Sales Cloud
How to Implement AI for Business Transformation
15Jan

How to Implement AI for Business Transformation

Harnessing the Power of AI for Business Transformation The age of artificial intelligence (AI) is here. How to Implement AI for Business Transformation? Once a niche technology confined to research labs and the realm of science fiction, AI has now become a mainstream force. Today, an estimated 35% of businesses are leveraging AI to enhance products, boost efficiency, and gain a competitive edge. However, for companies yet to begin their AI journey, the path to implementation can seem daunting. So how can organizations navigate the complexities of AI and unlock its potential to drive success? This comprehensive guide is designed to empower businesses to confidently adopt AI. We’ll break down what AI is, assess your organization’s readiness, help you develop a robust AI strategy, and explore how to implement and integrate AI across operations. Ultimately, this insight will show you how to embrace AI for continuous innovation, helping automate tasks, uncover insights, and future-proof your business. AI Era Demands an Intelligent Data Infrastructure AI consulting services and digital transformation partners like Tectonic underscore the technology’s immense value, helping organizations evaluate, implement, and scale AI initiatives. However, knowing where to start and who to trust can be challenging. This guide will provide best practices for planning and executing AI projects, helping you make informed decisions when selecting solutions and partners. By the end, your organization will be equipped with the knowledge and confidence needed to make AI a powerful competitive advantage. Understanding the AI Landscape Before diving into AI implementation, it’s important to understand what artificial intelligence is and the wide array of applications it offers. What is Artificial Intelligence? Artificial intelligence (AI) refers to software and machines designed to perform tasks that typically require human intelligence—such as visual perception, speech recognition, decision-making, and language translation. AI is already deeply integrated into many everyday products and services, including: Machine Learning Basics At the core of most AI systems is machine learning (ML), which involves training algorithms on vast datasets, enabling them to learn from examples without being explicitly programmed for every scenario. There are three main types of machine learning: Beyond ML, fields like natural language processing (NLP) focus on understanding human language, while computer vision analyzes visual content such as images and video. Real-World AI Applications Understanding the fundamentals of AI helps organizations align their needs with its capabilities. Common business use cases for AI include: Armed with this knowledge, businesses can better evaluate how AI fits into their goals and operations. Developing a Comprehensive AI Strategy Once you understand the AI landscape, the next step is developing a strategic plan to guide implementation. Establishing an AI Vision and Objectives AI adoption must align with clear financial and operational goals. Leadership teams should identify: Aligning stakeholders and executive leaders around specific use cases will drive urgency, investment, and commitment. AI Ethics and Governance AI adoption also requires guidelines for ethical usage, transparency, and accountability. Organizations should consider: Establishing these frameworks early ensures responsible and transparent AI usage. Resourcing an AI Program AI implementation requires the right talent and resources. Budget considerations should include: A Phased AI Adoption Roadmap Rather than attempting to scale AI all at once, organizations should adopt a phased approach: This roadmap balances short-term impact with long-term scalability. Choosing the Right AI Implementation Approach With your strategy in place, the next decision is how to implement AI. Three primary approaches are: The choice depends on your organization’s internal capabilities, desired level of customization, and timeline. Integrating AI into Your Operations Successful AI implementation requires careful planning and integration with existing operations. Develop an Integration Plan Consider how AI will interact with existing systems and workflows: Address Security and Privacy Ensure that AI systems comply with data privacy regulations and security protocols, especially when handling sensitive information. Drive Adoption Through Training Help staff understand how AI will augment their roles by providing training on how the algorithms work and how to interact with AI systems effectively. Monitor for Model Decay Implement processes to monitor and retrain models as needed to ensure continued performance and reliability. Embracing AI for Continuous Improvement AI should be viewed as an ongoing investment, driving continuous improvement across the organization. Encourage a Data-Driven Culture Empower teams to identify new AI use cases and experiment with AI-driven solutions. Provide the tools and frameworks to facilitate this culture of innovation. Foster Responsible AI Ensure that AI systems are transparent, accountable, and designed to augment human decision-making responsibly. Commit to Reskilling As AI capabilities evolve, continually upskill employees to ensure your workforce remains at the forefront of technological advancements. Unlocking the Future of AI The potential of AI to revolutionize businesses is clear. However, achieving success requires more than just technical capabilities. It demands thoughtful planning, strategic alignment, and a commitment to continuous improvement. By following this guide, your organization can confidently implement AI to unlock powerful data-driven insights, automate tasks, and achieve lasting competitive advantage. The future of AI is full of possibilities—are you ready to seize them? Tectonic is ready to help. How to Implement AI for Business Transformation Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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January 15, 2024in Artificial Intelligence, Data, Google, Technology
Improve Customer Experience
07Jan

Improve Customer Experience

The Importance of Customer Experience: Turning Every Interaction into a Lasting Impact Customer experience (CX) refers to every interaction a customer has with your brand—from the first touchpoint through to post-purchase support. While the term is often used broadly, its meaning is more nuanced, encompassing the entire customer journey. From the initial ad they see to the quality of their engagement with your customer support, CX reflects the customer’s perception of your brand, compared to the promises you’ve made. Improve Customer Experience. What Is Customer Experience (CX)? At its core, CX measures how customers perceive their interactions with your organization. It goes beyond customer service and spans every touchpoint, whether it’s the ease of navigating your website, the tone of your marketing emails, or the post-purchase support experience. A strong customer experience is critical for fostering brand loyalty and meeting customer expectations at every step of their journey. Why Customer Experience Matters In today’s competitive marketplace, customer expectations are at an all-time high. According to research, 80% of customers say that the experience a company provides is just as important as its products or services. Whether you’re in B2C or B2B, an exceptional customer experience translates into loyalty, brand advocacy, and revenue growth. Some key benefits of prioritizing CX include: Key Elements of a Great Customer Experience Our research highlights several factors that customers deem essential for a great experience: However, many companies fall short of these expectations. For example, 56% of customers report needing to repeat themselves to different representatives, and 55% say it feels like they’re interacting with separate departments rather than a single, unified brand. The good news? A subpar experience can be quickly remedied with exceptional customer service—75% of customers will forgive mistakes after receiving excellent support. How to Measure Customer Experience Measuring CX is essential for understanding what works and where improvements are needed. Popular methods include: Building a Successful CX Management Strategy An effective CX management strategy aligns your entire business around the customer’s needs. It should include continuous feedback loops, data-driven decision-making, and a focus on creating a customer-centric culture. Improve Customer Experience. Key Pillars of a CX Strategy: How to Improve Customer Experience Delivering a standout customer experience requires a combination of people, processes, and technology. Here are five best practices for enhancing your CX: The Role of Experience Management Customer experience management (CXM) goes hand-in-hand with a broader experience management strategy. This includes not only customer interactions but also employee experiences, product quality, and brand perception. By implementing an experience management framework, companies can align technology, culture, and six core competencies to optimize all aspects of customer engagement. The Bottom Line: Customer Experience Drives Success With Salesforce Customer experience is no longer just a buzzword—it’s a critical factor for business success. By understanding and improving the customer journey, you can foster loyalty, reduce churn, and create a long-term competitive advantage. Start by building a strong CX framework, empowering your teams, and making data-driven decisions to lead the way in customer satisfaction. Content updated August 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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January 7, 2024in Data, Google, Marketing Automation, Salesforce Copilots, Technology
Generative AI Trends for 2024
31Dec

Generative AI Trends for 2024

It’s hard to believe that ChatGPT is only a year old. The number of exciting new product launches over the past 12 months has been astonishing — and there’s no sign of slowing down. In fact, quite the opposite. Earlier in November, OpenAI hosted DevDay, where the company announced extensive offerings across B2C and B2B markets. Cohere has doubled down on its knowledge search capabilities and private deployments. Amazon Web Services launched PartyRock, its no-code gen AI app-building playground. Generative AI Trends for 2024 you can expect to see. We believe that last month’s activity sets the stage for 2024 in the gen AI space. Here are six major trends happening across the space: While the technology’s possibilities continue to grow, we believe there are four principles for CEOs to consider as they drive their gen AI agendas. These principles draw from our experiences building gen AI applications with our clients throughout the year, as well as decades of delivering digital and analytics transformations. Be Intentional: Set Gen AI Strategy Top-Down Gen AI is a gold rush. Everyone from shareholders to employees to boards is scrambling to deploy the latest and most powerful gen AI tools, and many large organizations have over 150 gen AI use cases on backlog. While we share their excitement and admire their ambition, allowing dozens of gen AI projects to spawn across an organization puts at-scale value creation at risk. Generative AI Trends for 2024 With recent developments in the gen AI space, the proliferation of use cases and opportunities will continue to split the already divided attention of leadership teams. C-suites must bring focus with a top-down gen AI strategy, constantly asking how the technology can create enduring strategic distance between the organization and its competitors. Here are some examples from first movers: Smart organizations are taking a 2×2 approach: identifying two fast use cases to register quick wins and excite the organization while working on two slower, more transformational use cases that will change day-to-day business operations. Reimagine Entire Domains Rather Than Isolated Use Cases During 2023, most organizations began experimenting with gen AI, building one-off prototypes and buying off-the-shelf solutions. Yet, as these solutions are rolled out to end users, organizations are struggling to capture value. For example, some organizations that invested in GitHub Copilot have yet to figure out how the value capture is passed back to the business. Organizations need to reframe from isolated use cases to the full software delivery lifecycle. Scrum teams need to commit to shipping more product features, or sales need to offer more competitive pricing to win more business. Stopping at just buying a new shiny tool means the productivity gains will not translate to bottom-line gains. This often means reimagining entire workflows and domains. This serves two purposes: 1) it creates a more seamless end-user experience by avoiding point solutions; and 2) organizations can more easily track value against clear business outcomes. For example, an insurer we worked with is reimagining its end-to-end claims process — from first notice of loss to payment. For each step along the way, the insurer has identified gen AI, digital, and analytics opportunities, while never losing sight of the claims adjuster’s experience. Ultimately, this comprehensive approach made a step-change impact on end-to-end handling time. Buy Selectively, Build Strategically Matching the pace of innovation, many new startups and software offerings are entering the market, leaving enterprises with a familiar question: “Buy or build?” On the “buy” side, organizations are wary about investing in capabilities that will eventually be available for a fraction of the cost. These organizations are also skeptical of off-the-shelf solutions, unsure if the software will perform at scale without significant customization. As these solutions mature and prove their value, “buy” strategies will continue to play a central role in any gen AI strategy. Meanwhile, some organizations find compelling business cases to “build.” These players start by identifying use cases that create strategic competitive advantages against their peers by compounding existing strengths in their domain expertise, workflow integration, or regulatory know-how. For example, deploying gen AI to accelerate drug discovery has become standard in the pharmaceutical industry. Additionally, organizations are investing in data and IT infrastructure to enable their portfolio of gen AI use cases. For many organizations, there has been little to no investment in unstructured data governance. Now is the time. Build Products, Not Proofs of Concept (POCs) With the new tooling available, a talented engineer can build a proof-of-concept over a weekend. In some cases, this might be sufficient to serve an enterprise need (e.g., a summarization chatbot). However, for most use cases in a large enterprise context, proofs-of-concept are not sufficient. They do not scale well into production and their performance degrades without the appropriate engineering and experimentation. At OpenAI’s Dev Day, engineers demonstrated how hard it is to turn a POC into a production-grade product. Initially, a demo POC only achieved 45% accuracy for a retrieval task. After a few months and numerous experiments (e.g., fine-tuning, re-ranking, metadata tagging, data labeling, model self-assessment, risk guardrails), the engineers achieved 98% accuracy. Implications of Generative AI Trends for 2024 This has two implications. First, organizations cannot seek near-perfection on every use case. They need to be selective about when it is worthwhile to invest scarce engineering talent to develop high-performance gen AI applications. For some situations, 45% accuracy may be sufficient to deliver business benefits. Second, organizations need to scale their gen AI capabilities to meet their ambitions. Most organizations have identified hundreds of gen AI use cases. Therefore, organizations are turning to reusable code components to accelerate development. Dedicated engineers, often in a Center of Excellence (COE), codify best practices into these code components, allowing subsequent gen AI efforts to build off the lessons learned from pioneering projects. We have seen these components accelerate delivery by 25% to 50%. Throughout the past year, there has been an endless stream of gen AI news and hype. The coming year will likely be similar

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December 31, 2023in Generative AI
Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities
14Dec

Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities

Salesforce (NYSE: CRM) has announced major updates to its Einstein 1 Platform, introducing the Data Cloud Vector Database and Einstein Copilot Search. These new features aim to power AI, analytics, and automation by integrating business data with large language models (LLMs) across the Einstein 1 Platform. Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities. Unifying Business Data for Enhanced AI The Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data. This will enable accurate and relevant AI prompts and Einstein Copilot, eliminating the need for expensive and complex fine-tuning of LLMs. Built into the Einstein 1 Platform, the Data Cloud Vector Database allows all business applications to harness unstructured data through workflows, analytics, and automation. This enhances decision-making and customer insights across Salesforce CRM applications. Introducing Einstein Copilot Search Einstein Copilot Search will provide advanced AI search capabilities, delivering precise answers from the Data Cloud in a conversational AI experience. This feature aims to boost productivity for all business users by interpreting and responding to complex queries with real-time data from various sources. Key Features and Benefits Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities Data Cloud Vector Database Einstein Copilot Search Addressing the Data Challenge With 90% of enterprise data existing in unstructured formats, accessing and leveraging this data for business applications and AI models has been challenging. As Forrester predicts, the volume of unstructured data managed by enterprises will double by 2024. Salesforce’s new capabilities address this by enabling businesses to effectively harness their data, driving AI innovation and improved customer experiences. Salesforce’s Vision Rahul Auradkar, EVP and GM of Unified Data Services & Einstein, stated, “The Data Cloud Vector Database transforms all business data into valuable insights. This advancement, coupled with the power of LLMs, fosters a data-driven ecosystem where AI, CRM, automation, Einstein Copilot, and analytics turn data into actionable intelligence and drive innovation.” Practical Applications Customer Success Story Shohreh Abedi, EVP at AAA – The Auto Club Group, highlighted the impact: “With Salesforce automation and AI, we’ve reduced response time for roadside events by 10% and manual service cases by 30%. Salesforce AI helps us deliver faster support and increased productivity.” Availability Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities Salesforce’s new Data Cloud Vector Database and Einstein Copilot Search promise to revolutionize how businesses utilize their data, driving AI-powered innovation and improved customer experiences. Salesforce Enhances Einstein 1 Platform with New Vector Database and AI Capabilities Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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December 14, 2023in Einstein 1 Platform, Salesforce
Cool New AI Tools
27Nov

Cool New AI Tools

In the rapidly growing world of artificial intelligence, staying abreast of the latest tools is not merely advantageous but imperative. As AI technology advances, so do the instruments that revolutionize problem-solving, innovation, and business growth. Whether you are an experienced developer, an aspiring entrepreneur, or simply interested in the expansive potential of AI, this insight offers a comprehensive guide to the newest and most impactful AI tools available. Additionally, startups and developers can now register their AI projects at no cost by visiting genai.works. Let us dig into this exciting wave of innovation. AI Tools Overview AI for Content & Voiceovers Parlandi AI: Accessible at parlandi.com, this tool enables the generation of various text content such as articles, blogs, advertisements, and media in 53 languages. Additionally, users can create AI-generated images by simply describing them, leveraging solutions like OpenAI DALL-E-2, DALL-E-3, DALL-E-3 HD, and Stable Diffusion by Stability.ai. AI for Clip Generation 10LevelUp: Available at 10levelup.com, this platform automates the creation of viral clips from YouTube videos, facilitating channel growth with minimal user input by generating engaging clips within minutes. AI for In-Depth Qualitative Research ResearchGOAT: Found at researchgoat.com, ResearchGOAT harnesses the burgeoning capabilities of generative AI to design, field, and analyze custom research studies across various vertical markets, geographical regions, and consumer cohorts. AI for Customer Support ChatFly: Accessible via chatfly.co, ChatFly is a robust platform for developing AI-driven chatbots. It empowers businesses to create intelligent bots using their data, which can be seamlessly integrated into existing systems to enhance customer support. AI to Automate Document Processes Base64.ai Document AI: Available at base64.ai, this leading no-code AI solution comprehends documents, photos, and videos, facilitating the automation of document-related processes. AI for Job & CV Management Xtramile: Accessible through lnkd.in, Xtramile offers an Office Add-in that allows the dissemination of job offers across job boards with a single click, streamlining the recruitment process. Conclusion Empower your operations and innovate with these cutting-edge AI tools, tailored to meet a variety of business needs from content creation and customer support to qualitative research and job management. Embrace the future of AI and unlock new potentials for growth and efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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November 27, 2023in Generative AI, Salesforce Einstein
AI Transparency
13Oct

AI Transparency Explained

Understanding AI Transparency AI transparency is about making the inner workings of an AI model clear and understandable, allowing us to see how it arrives at its decisions. It involves a variety of tools and practices that help us comprehend the model, the data it’s trained on, how errors and biases are identified and categorized, and how these issues are communicated to developers and users. As AI models have become more advanced, the importance of transparency has grown. A significant concern is that more powerful models are often more opaque, leading to the so-called “black box” problem. “Humans naturally struggle to trust something they can’t understand,” said Donncha Carroll, partner and chief data scientist at Lotis Blue Consulting. “AI hasn’t always proven itself to be unbiased, which makes transparency even more critical.” Defining AI Transparency AI transparency is essential for building trust, as it allows users to understand how decisions are made by AI systems. Since AI models are trained on data that can carry biases or risks, transparency is crucial for gaining the trust of users and those affected by AI decisions. “AI transparency is about clearly explaining the reasoning behind the output, making the decision-making process accessible and comprehensible,” said Adnan Masood, chief AI architect at UST. “It’s about demystifying AI and providing insight into its decision-making process.” Transparency is becoming increasingly vital due to its role in fostering trust, enabling auditability, ensuring compliance, and helping to identify and address potential biases. Without it, AI systems risk perpetuating harmful biases, making opaque decisions, or causing unintended consequences in high-risk scenarios, Masood added. Explainability and Interpretability in AI Transparency AI transparency is closely related to concepts like explainability and interpretability, though they are distinct. Transparency ensures that stakeholders can understand how an AI system operates, including its decision-making and data processing. This clarity is essential for building trust, especially in high-stakes applications. Explainability, on the other hand, provides understandable reasons for AI’s decisions, while interpretability refers to how predictable a model’s outputs are based on its inputs. While both are crucial for achieving transparency, they don’t fully encompass it. Transparency also involves openness about how data is handled, the model’s limitations, potential biases, and the context of its usage. Ilana Golbin Blumenfeld, responsible AI lead at PwC, emphasized that transparency in process, data, and system design complements interpretability and explainability. Process transparency involves documenting and logging key decisions during system development and implementation, while data and system transparency involves informing users that an AI or automated system will use their data, and when they are interacting with AI, like in the case of chatbots. The Need for AI Transparency AI transparency is crucial for fostering trust between AI systems and users. Manojkumar Parmar, CEO and CTO at AIShield, highlighted the top benefits of AI transparency: Challenges of the Black Box Problem AI models are often evaluated based on their accuracy—how often they produce correct results. However, even highly accurate models can be problematic if their decision-making processes are opaque. As AI’s accuracy increases, its transparency often decreases, making it harder for humans to trust its outcomes. In the early days of AI, the black box problem was somewhat acceptable, but it has become a significant issue as algorithmic biases have been identified. For example, AI models used in hiring or lending have been found to perpetuate biases based on race or gender due to biased training data. Even highly accurate models can make dangerous mistakes, such as misclassifying a stop sign as a speed limit sign. These errors highlight the importance of understanding how AI reaches its conclusions, especially in critical applications like healthcare, where a misdiagnosis could be life-threatening. Transparency in AI makes it a better partner for human decision-making. In regulated industries, like banking, explainability is often a legal requirement before AI models can be deployed. Similarly, regulations like GDPR give individuals the right to understand how decisions involving their private data are made by AI systems. Weaknesses of AI Transparency While AI transparency offers many benefits, it also presents challenges: As AI models continuously evolve, they must be monitored and evaluated to maintain transparency and ensure they remain trustworthy and aligned with their intended outcomes. Balancing AI Transparency and Complexity Achieving AI transparency requires a balance between different organizational needs. When implementing AI, organizations should consider the following factors: Best Practices for Implementing AI Transparency Achieving AI transparency requires continuous collaboration and learning within an organization. Leaders and employees must clearly understand the system’s requirements from a business, user, and technical perspective. Blumenfeld suggests that providing AI literacy training can help employees contribute to identifying flawed responses or behaviors in AI systems. Masood recommends prioritizing transparency from the beginning of AI projects. This involves creating datasheets for datasets, model cards for models, rigorous auditing, and ongoing analysis of potential harm. Key Use Cases for AI Transparency AI transparency has many facets, and teams should address each potential issue that could hinder transparency. Parmar suggests focusing on the following use cases: The Future of AI Transparency AI transparency is an evolving field as the industry continually uncovers new challenges and develops better processes to address them. “As AI adoption and innovation continue to grow, we’ll see greater AI transparency, especially in the enterprise,” Blumenfeld predicted. However, approaches to transparency will vary based on the needs of different industries and organizations. Carroll anticipates that AI transparency efforts will also be shaped by factors like insurance premiums, particularly in areas where AI risks are significant. These efforts will be influenced by an organization’s overall system risk and evidence of best practices in model deployment. Masood believes that regulatory frameworks, like the EU AI Act, will play a key role in driving AI transparency. This shift toward greater transparency is crucial for building trust, ensuring accountability, and responsibly deploying AI systems. “The journey toward full AI transparency is challenging, with its share of obstacles,” Masood said. “But through collective efforts from practitioners, researchers, policymakers, and society, I’m optimistic that

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October 13, 2023in Salesforce
Salesforce High Velocity Sales
02Sep

Salesforce High Velocity Sales

Exploring High Velocity Sales (HVS) in Today’s Business Landscape In the fast-paced world of business, sales departments are constantly seeking strategies to enhance efficiency and boost revenue. One approach gaining significant traction is High Velocity Sales (HVS). This guide offers a comprehensive overview of HVS, its impact on sales processes, and how Salesforce has revolutionized this high-speed approach. Understanding High Velocity Sales High Velocity Sales (HVS) is a Salesforce Sales Cloud extension that enables inside sales teams to prioritize hot leads, boost conversion rates, and build and sustain new business opportunities. Recently renamed to Sales Engagement, this extension includes automation features such as customer engagement tracking, chatbots, cadences, and automated actions. HVS emphasizes speed and efficiency in the sales funnel, leveraging automation and data-driven insights to streamline processes, accelerate lead conversion, and drive revenue growth. As competition intensifies and customer expectations evolve, adopting HVS has become essential for businesses aiming to stay competitive. Key Updates and Features Salesforce’s Role in High Velocity Sales Salesforce, a leading CRM platform, has transformed sales workflows with its HVS capabilities. By integrating HVS into the Salesforce platform, businesses gain access to advanced automation tools, intelligent lead scoring, and personalized engagement at scale. This integration empowers sales teams to identify and prioritize high-quality leads, automate tasks, and optimize sales efforts, driving revenue growth and enhancing sales performance. Benefits of High Velocity Sales Implementing HVS offers numerous benefits to organizations: Challenges and Considerations While HVS provides significant advantages, it may not suit every sales process, especially those with complex, long-term cycles. Adopting HVS can involve a learning curve, and there’s a risk of sacrificing quality interactions with prospects for the sake of speed. Balancing velocity with relationship-building is crucial for long-term success. Alternative Solutions and Integration Exploring alternative sales engagement tools beyond Salesforce HVS can offer unique features tailored to specific business needs. Ensuring seamless integration with existing systems and processes is essential to maximize efficiency and workflow. Choosing Your Sales Engagement Tool When selecting a sales engagement tool, consider factors such as: Evaluating the potential return on investment is critical to making an informed decision. Embracing Innovation in Sales In today’s competitive business environment, embracing innovative sales strategies like High Velocity Sales is crucial. Leveraging automation, data-driven insights, and streamlined workflows, businesses can enhance productivity, increase efficiency, and achieve remarkable sales results. Ready to Revolutionize Your Sales Process? Explore High Velocity Sales and unlock your sales team‘s full potential with Salesforce and other cutting-edge technologies. Reach out to learn how Salesforce HVS can transform your sales process and schedule a consultation with experts at Tectonic to explore comprehensive solutions tailored to your business needs. Content updated March 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 2, 2023in Salesforce, Salesforce Optimization, Salesforce Sales Cloud
Einstein in Salesforce
26Aug

Einstein in Salesforce

Salesforce AI and CRM Evolution Salesforce has long been a leader in customer relationship management (CRM) by pioneering cloud technologies. Recently, the platform has significantly advanced with the integration of generative artificial intelligence (AI) and AI-powered features, thanks to its Einstein technology. Einstein in Salesforce is like a super smart computer overseeing and analyzing the data in your CRM. This guide explores Salesforce’s AI strategy, exploring its specific products and features to help business teams understand and benefit from this technology. Exploring Salesforce’s Advanced AI Features Einstein, Salesforce’s AI technology, powers various advanced features within the platform. This guide will cover these capabilities, provide real-life adoption examples, and discuss their benefits. Additionally, it offers best practices, solutions, and services to facilitate your Einstein implementation. Salesforce’s Comprehensive CRM Solution Salesforce remains a number one in the CRM software world, offering robust solutions for managing relationships across various departments. Specific clouds within Salesforce enable teams to handle marketing, sales, customer service, e-commerce, and more. The platform focuses on customer experience and provides robust data analytics to support decision-making. Enhancements Through Generative AI Salesforce’s generative AI has rapidly enhanced the platform’s automation, workflow management, data analytics, and assistive capabilities for customer management. A prime example is Salesforce Copilot, which aids internal users with outreach and analysis tasks while improving the external user experience. What is Salesforce Einstein? Salesforce Einstein is the first comprehensive AI for CRM, integrating AI technologies to enhance the Customer Success Platform and bring AI to users everywhere. It is seamlessly integrated into many Salesforce products, offering generative AI built specifically for CRM. Key Features of Salesforce Einstein Comprehensive AI Capabilities of Salesforce Einstein Einstein extends its capabilities across the Salesforce CRM platform under the Customer 360 umbrella, enhancing intelligence and providing personalized customer experiences. Key Benefits of Salesforce Einstein Salesforce Einstein helps close deals faster, personalize customer service, understand customer behaviors, target audience segments better, and create personalized shopping experiences. It ensures data protection and privacy through the Einstein Trust Layer, maintaining strong data governance controls. Responsible AI Principles Salesforce is committed to responsible AI principles, ensuring Einstein is trustworthy and safe for every organization. Organizations can select from various principles to ensure ethical AI use in their operations. Implementation of Salesforce Einstein Salesforce Einstein is a powerful AI solution transforming how businesses interact with customers. By leveraging machine learning and data analysis, it personalizes experiences, predicts customer behavior, and automates tasks, boosting sales, enhancing service, and driving growth. As AI evolves, its impact on CRM will continue to grow, making it an indispensable tool for businesses aiming to stay competitive in today’s data-driven landscape. Top 4 Benefits of Salesforce Einstein in an Organization Einstein Essentials Salesforce Einstein and GPT (Generative Pretrained Transformer) technologies represent significant advancements in AI, particularly in CRM and natural language processing. Here’s a brief overview of their relevance and potential intersection: Data Handling and Ethics in Salesforce Salesforce manages a vast amount of customer data, and the ethical handling of this data is crucial. Key considerations include data privacy, secure storage, access controls, compliance with regulations like GDPR and CCPA, and the ethical use of AI and machine learning. It’s important to maintain transparency, avoid biases, and ensure AI models are making ethical decisions. Newest Einstein Features for 2024 In the rapidly evolving ecosystem of Salesforce, AI offers a suite of tools to spark innovation, streamline operations, and provide richer business insights. Explore these potentials and let Einstein AI reshape your work in 2024. Content updated June 2024. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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August 26, 2023in Einstein 1 Platform, Generative AI, Salesforce Data Cloud, Salesforce Einstein
Salesforce Service Cloud Einstein
09Mar

Salesforce Service Cloud Einstein

Einstein for Service is a robust suite of time-saving Artificial Intelligence features designed to empower agents in delivering exceptional customer service experiences. Salesforce Service Cloud Einstein-learn more. Customer service has evolved from being a cost center to a growth driver, and leading companies are prioritizing customer service to increase brand loyalty. In Service Cloud Einstein, various AI technologies, such as Machine Learning (ML), deep learning, predictive analytics, Natural Language Processing (NLP), and smart data discovery, work collaboratively to enhance customer support, providing faster and better service. Salesforce Einstein, recognized as the world’s first “generative AI” built for CRM, seamlessly integrates into multiple Salesforce products, including Marketing Cloud, Sales Cloud, and Service Cloud. Sales Cloud incorporates Einstein in the form of eight essential tools: Salesforce Einstein, since its inception in 2016, has been at the forefront of CRM AI technology, delivering personalized and predictive experiences for enhanced professionalism. Salesforce Service Cloud is a CRM platform focused on providing service and support to business customers. It is an extension of the Sales Cloud product tailored for sales professionals. Service Cloud Einstein is utilized by notable companies like Thomson Reuters, Southern Glazer’s Wine and Spirits, Cisco, and Skillsoft. Service Cloud Einstein benefits businesses by providing efficient customer service, with Einstein GPT responding promptly to inquiries, offering precise responses, enhancing customer satisfaction, and reducing resolution time. Studies show that in the same time 3 customers could be serviced before Service Cloud Einstein, now ten can be taken care of. The difference between Einstein GPT and ChatGPT lies in their design, with Einstein GPT specifically tailored for Salesforce users and clouds, while ChatGPT is a more versatile model for general use. Einstein is available for free with Salesforce’s Developer Edition, providing access to most platform features for building and testing custom applications and integrations using Einstein. Salesforce Sales Cloud and Service Cloud differ in their focus, with Sales Cloud concentrating on sales processes, while Service Cloud centers around customer service and support. Einstein remains the overarching AI brand for Salesforce, present across the portfolio, including within Tableau. Einstein Discovery is available as part of Tableau CRM Plus or through Einstein Predictions. Are you ready to explore the power of Einstein in your Salesforce Service Cloud implementation?  Contact Tectonic today. Tectonic is please to announce Salesforce Service Cloud Implementation Solutions. Content updated January 2024. Like1 Related Posts Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more CRM Cloud Salesforce What is a CRM Cloud Salesforce? Salesforce Service Cloud is a customer relationship management (CRM) platform for Salesforce clients to Read more

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March 9, 2023in Marketing Automation, Salesforce Einstein, Salesforce Service Cloud
Salesforce Solutions for Communications
14Feb

Salesforce Solutions for Communications

Salesforce has recently unveiled tailored Salesforce Solutions for Communications aimed at enhancing customer experiences through advanced analytics, automation tools, and AI-driven customer service. These innovations empower providers to gain deeper insights into their customers, automate interactions, and effectively monitor customer satisfaction levels. For communication providers looking to elevate their customer service, Salesforce’s automation solutions offer significant benefits. They ensure seamless and efficient handling of every customer interaction, leading to improved satisfaction and increased loyalty. Salesforce Solutions for Communication Providers Salesforce offers a comprehensive suite of solutions specifically designed for communication providers to enhance customer experiences. This suite includes: Salesforce Customer Engagement Platform (CXP) and Tools The Salesforce Customer Engagement Platform equips communication providers with a suite of tools to enhance customer experiences, including: Salesforce Einstein AI Platform for Communication Providers The Salesforce Einstein AI Platform is tailored to improve customer experiences for communication providers by analyzing extensive datasets to identify patterns, understand customer needs, and optimize interactions, ultimately enhancing overall customer experience. Benefits of the Salesforce Customer Engagement Platform The Salesforce Customer Engagement Platform offers communication providers various benefits, including enhanced customer experience, increased sales, and improved operational efficiencies. Features such as social listening and engagement analytics enable providers to understand customer sentiment and behavior, facilitating personalized interactions and driving sales growth. New Salesforce Innovations for Communication Providers New innovations from Salesforce include analytics, AI, and prebuilt solutions that automate processes, improve customer experiences, and reduce operational costs. Integrations with WhatsApp enable richer customer engagements, personalized experiences, and automated interactions through chatbots. In conclusion, Salesforce’s solutions for communication providers represent a significant advancement in improving customer experiences, revolutionizing how providers interact with their clientele to achieve positive outcomes and business growth. Contact Tectonic today to explore Salesforce communications solutions. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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February 14, 2023in Salesforce, Salesforce Communications Cloud, Salesforce Einstein, Salesforce Sales Cloud, Salesforce Service Cloud

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